tsORFdb: Theoretical Small Open Reading Frames (ORFs) database and massProphet: Peptide Mass Fingerprinting (PMF) tool for unknown small functional ORFs

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• 作者：Hyoung-Sam Heo ; Sanghyuk Lee ; Ji Min Kim ; Yeon Ja Choi ; Hae Young Chung ; S. June Oh
• 关键词：Bioinformatics ; Database ; ORFeomics ; Peptide Mass Fingerprinting ; Proteomics ; sORFs (Small Open Reading Frames)
• 刊名：Biochemical and Biophysical Research Communications
• 出版年：2010
• 出版时间：18 June 2010
• 年：2010
• 卷：397
• 期：1
• 页码：120-126
• 全文大小：915 K

文摘

Peptide mass fingerprinting (PMF) has become one of the most widely used methods for rapid identification of proteins in proteomics research. Many peaks, however, remain unassigned after PMF analysis, partly because of post-translational modification and the limited scope of protein sequences. Almost all PMF tools employ only known or predicted protein sequences and do not include open reading frames (ORFs) in the genome, which eliminates the chance of finding novel functional peptides. Unlike most tools that search protein sequences from known coding sequences, the tool we developed uses a database for theoretical small ORFs (tsORFs) and a PMF application using a tsORFs database (tsORFdb). The tsORFdb is a database for ORFeome that encompasses all potential tsORFs derived from whole genome sequences as well as the predicted ones. The massProphet system tries to extend the search scope to include the ORFeome using the tsORFdb. The tsORFdb and massProphet should be useful for proteomics research to give information about unknown small ORFs as well as predicted and registered proteins.